AI Engineer

Capgemini

Atlanta (GA)

On-site

USD 56,000 - 90,000

Full time

8 days ago

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Benefits offered by this job

Medical

Dental

Vision

Retirement benefits

Job summary

Capgemini is seeking a hands-on AI Engineer in Atlanta, GA to enhance an AI platform built on Claude Sonnet and MCP. This contract role focuses on improving AI agents, MCP tools and servers, enterprise integrations, and platform quality, performance, security, and scalability.

You will work on MCP-based applications, expand core capabilities, and ensure production readiness through monitoring, logging, and risk controls, while collaborating with cross-functional teams.

Qualifications

3+ years of software development experience with Python and/or TypeScript/Node.js.
Hands-on experience building LLM / Generative AI applications.
Strong debugging, problem-solving, and communication skills.
Knowledge of MCP (Model Context Protocol), AI agents, and tool calling.
Experience with Claude, OpenAI, or similar LLM platforms.
Experience integrating APIs, databases, and enterprise applications.
Knowledge of RAG, vector databases, embeddings, and prompt engineering.

Responsibilities

Enhance and maintain MCP-based AI applications and agents.
Develop and improve MCP servers, tools, and integrations.
Integrate AI solutions with APIs, databases, and knowledge repositories.
Improve prompt engineering, context management, and response accuracy.
Build and optimize RAG solutions.
Implement monitoring, logging, security controls, and performance improvements.
Troubleshoot AI agent behavior, tool execution, and platform issues.
Support deployment, testing, and continuous enhancement of AI capabilities.

Skills

Python

TypeScript/Node.js

LLM / Generative AI

Tools

Claude Sonnet

OpenAI

LangChain

LangGraph

Semantic Kernel

Job description

Capgemini is seeking a hands-on AI Engineer in Atlanta, GA to enhance and optimize an existing AI platform built on Claude Sonnet and the Model Context Protocol (MCP). This is a contract role focused on improving AI agents, MCP tools and servers, enterprise integrations, and the overall quality, performance, security, and scalability of the platform.

Role Overview

You will work directly on MCP-based AI applications and agents, expanding core platform capabilities and strengthening end-to-end behavior. The role emphasizes improved context handling, reliable tool execution, and production readiness through monitoring, logging, security controls, and performance enhancements.

Responsibilities

Enhance and maintain MCP-based AI applications and agents
Develop and improve MCP servers, tools, and integrations
Integrate AI solutions with enterprise systems, APIs, databases, and knowledge repositories
Improve prompt engineering, context management, and response accuracy
Build and optimize RAG (Retrieval-Augmented Generation) solutions
Implement monitoring, logging, security controls, and performance improvements
Troubleshoot AI agent behavior, tool execution, and platform issues
Support deployment, testing, and continuous enhancement of AI capabilities

Required Qualifications

3+ years of software development experience using Python and/or TypeScript/Node.js
Hands-on experience building LLM / Generative AI applications
Strong understanding of MCP (Model Context Protocol), AI agents, and tool calling
Experience with Claude, OpenAI, or similar LLM platforms
Experience integrating APIs, databases, and enterprise applications
Knowledge of RAG, vector databases, embeddings, and prompt engineering
Strong debugging, problem-solving, and communication skills

Preferred Skills

Experience with LangChain, LangGraph, Semantic Kernel, or similar frameworks
Experience with AI observability, evaluation frameworks, and prompt optimization
Knowledge of security, authentication, and access control for AI applications
Experience deploying production-grade AI solutions

Technologies

Claude Sonnet, Model Context Protocol (MCP), TypeScript, Node.js, Python, LLM / Generative AI, RAG (Retrieval-Augmented Generation), vector databases, embeddings, LangChain, LangGraph, Semantic Kernel

Compensation and Work Details